Day 1 - Observed Climate Trends and Projected Climate Change … · Payong PAGASA PAGASA The...

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PAGASAThe Weather and Climate Authority

Observed

Climate Trendsand projected

Climate Changein the Philippines

Presented by:Thelma A. CincoAssistant Weather Services Chief

Philippine Atmospheric, Geophysical and Astronomical Services Administration

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Outline• Observed Trends: Global and the Philippines

• Climate Projections: SRES– and RCP– based climate projections

• Using the Climate Risk Analysis Matrix

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Distinguishing the difference

Weather• Is a specific meteorological

event or condition that happens over a period of hours or a few days.

Climate• The average weather

conditions over a long period of time (typically 30 years).

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Weather and climate information being provided by PAGASA

Past Present Future

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The SW and NE monsoons in the Philippines

June-July-August October-November-December

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Climate variability refers to shorter term fluctuations in climate such as those caused by the El Niño Southern Oscillation (ENSO) Phenomenon.

What is Climate variability?

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El Niño La Niña

Source: http://www.esrl.noaa.gov

El Niño Southern Oscillation(ENSO)

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El Niño affects several regions across the globe

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Some of the Impacts of El Niño in the Philippines

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Some of the Impacts of La Niña in the Philippines

Landslide :Ginsaugon, Feb 2006

ST. BERNARD LANDSLIDE

Feb 2006

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Climate Change?Is that really happening?

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Global warming: Indicative of climate changeIs Global Temperature Rising?

0.85°C 1880-2012(IPCC AR5)

Source: IPCC AR5 WG1

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Global warming: Indicative of climate changeIs Global Temperature Rising?

Earth’s Long Term (1880-2016) Warming Trend (5-year average)

Source: National Aeronautics and Space Administration

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2016 global mean temperature is a record high

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August 2017 is the second highest

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DOST-PAGASAThe Weather and Climate Authority

Latest from WMO

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What are the ObservedClimate Trends in the

Philippines ?

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Observed climate trends in the Philippines:Over the past 65 years (1951-2015), a 0.68˚C increase in annual mean temperature has been observed

0.24˚C annual maximum temperature increase

0.99˚ C annual minimum temperature increase

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Wetting/drying tendency of annual total rainfall in the Philippines (1951-2010)

• Parts of central and northern Luzon

• Parts of eastern Visayas

• Northeastern and southwestern sections Mindanao

• Northern sections of Luzon

• Parts of western Visayas

• Central and western sections Mindanao

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Dec-Jan-Feb Mar-Apr-May Jun-Jul-Aug Sep-Oct-Nov

Increasing and decreasing trends in seasonal rainfall (1951-2010)

Source: IAAS, 2016

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Increasing number of hot days and decreasing cold nights

Source: Cinco et al. 2014

Hot days Cold Nights

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Increasing frequency of extreme rainfall events (1951–2010)

Intensity Frequency

Source: Cinco et al. 2015

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Source: Cinco et al., 2016

Slightly decreasing in number of Tropical Cyclones TCs

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Slightly increasing number of intense TCs (maximum sustained winds >170kph)

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Frequency of Tropical Cyclones which crossed the Metro Manila for the period 1948 to 2016

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Will those changes continue in the future?

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Understanding the difference

Weather forecast• The state of the atmosphere

(or the weather situation) at a particular location over a short period of time

• Highly dependent on the initial state of the atmosphere and the upper ocean

Climate projection• A likelihood of something to

happen in climate several decades or centuries in the future

• Conditional climate expectations based on scenarios (e.g., increase in green house gases)

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ClimateProjections

Understanding how

are made

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SCEN

ARIO SRES - Special Report on

Emissions Scenarios RCP – Representative Concentration Pathways

DESC

RIPT

ION Socio-economic driven scenarios Emission-driven scenarios

Describes a wide range of potential futures for the main drivers of climate change –greenhouse gases, air pollutant emissions & land use

BASE

S

• Demography• Economic development• Regionalization• Energy production/use• Technology • Agriculture• Forestry• Land use

RADIATIVE FORCINGRCP scenarios are new scenarios that specify concentrations and corresponding emissions,

(No fixed sets of assumptions related to population growth, economic development, ortechnology associated with any RCP)

NAM

ES A1, A2, B1, B2 families RCP 2.6, 4.5, 6.0, 8.5 (Wm-2)

Different scenarios

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Source: IPCC AR5 WG1

SRES vs RCP

RC

P 8.

5 Rising radiative forcing pathway leading to 8.5 W/m² in 2100.

RC

P 6

Stabilization without overshoot pathway to 6 W/m² at stabilization after 2100

RC

P 4.

5

Stabilization without overshoot pathwayto 4.5 W/m² at stabilization after 2100

RC

P 2.

6 Peak in radiative forcing at ~ 3 W/m² before 2100 and decline

Comparison of CO2 concentrations from SRES (A1B, A1FI, A2, B1) and RCP (RCP 3, RCP 4.5, RCP 6, RCP 8.5)

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1.6°C (2036-2065)MDGF Report – SRES A1B1.4°C – 2.0°C (2030-2059)SEACAM Report0.9°C – 1.9°C (2036-2065)7 model simulations*1.2°C – 2.3°C (2036-2065)12 model simulations

SUMMARY of CHANGESScenario Mid-21st century End of the 21st century

A1B +1.4 to +2.0 +2.7 to +3.8RCP4.5 +0.9 to +1.9 +1.3 to +2.5RCP8.5 +1.2 to +2.3 +2.5 to +4.1

Projected Annual Mean Temperature Change*

*relative to 1971 to 2000

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Possible risks associated with warmer temperature

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Projected changes in seasonal total rainfall by the Mid-21st

Century (2036-2065) based on RCP8.5 scenario

Driest Possible

Median

Wettest Possible

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Possible risk associated with increased/enhanced rainfall in the future

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Possible risk associated with drier condition in the future

Source: http://opinion.inquirer.net

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Projected future change in tropical cyclones to affect the Philippines

Source: Daron et al. 2016, DFID project, UK- Met-office report

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Some of the Impacts of strong tropical cyclones

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So, what can we do now to make our families, communities,

businesses, and our whole locality resilient to

climate variability and change?

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Link of DRR and CCA

CCA and DRR: point of conceptual convergence (Source: Gotangco 2012)

Climate Change Adaptation:

Reduce risk to:

Gradual changes in climatic parameters

Extreme weather event with increased frequency and severity

Hazards that are associated with changing climate “Normals”

Hazards that are associated with extreme events

Disaster Risk Management

Reduce risk to:

Sea Level Rise

Changes in mean Temperature

Changes in Precipitation patterns

Climate and weather related events

GeophysicalEvents

Ecological Events

Other events (e.g. technological, terrestrial

Direct connection

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Climate Change Impacts

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Driest Possible

Median

Projected changes in seasonal rainfall over Eastern Samar by the Mid-21st Century (2036-2065) based on RCP8.5 scenario

Wettest Possible


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How to Utilize the Climate Risk Analysis Matrix CLIRAM

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Percent (%) Rainfall amount (mm)

Lower Bound -4.2 -41.1 945.9Median 1.3 12.5 999.5

Upper Bound 45.0 444.4 1431.4Lower Bound -7.9 -77.8 909.2

Median 13.7 135.2 1122.2Upper Bound 43.6 430.8 1417.8Lower Bound -2.6 -12.1 452.0

Median 1.8 8.2 472.3Upper Bound 17.4 80.8 544.9Lower Bound 5.8 26.8 490.9

Median 1.1 5.3 469.4Upper Bound 13.0 60.3 524.4Lower Bound -6.7 -37.5 522.3

Median -1.1 -6.0 553.8Upper Bound 8.3 46.4 606.2Lower Bound -14.0 -78.3 481.5

Median -0.6 -3.2 556.6Upper Bound 9.7 54.6 614.4Lower Bound -20.1 -174.9 696.5

Median -16.6 -144.7 726.7Upper Bound -3.8 -33.4 838.0Lower Bound -22.0 -191.3 680.1

Median -9.3 -81.3 790.1Upper Bound 4.7 40.7 912.1

* upper: 90th percentile; median: 50th percentile; lower: 10th percentile

September-October-November (SON)

Observed baseline = 871 mm

Moderate Emission (RCP4.5)

High Emission (RCP8.5)

June-July-August (JJA)

Observed baseline = 560 mm



March-April-May (MAM)

Observed baseline =

464 mm



December-January-February (DJF)

Observed baseline =

987 mm



Projected Changes in Seasonal Rainfall in the Mid-21st Century (2036-2065) for Eastern Samar relative to 1971-2000

Adaptation OptionSeason Scenario Range*

Projected ChangeProjected Seasonal

Rainfall Amount (mm)

Potential ImpactsInformation about patterns of Change

Climate Risk Analysis Matrix CLIRAM

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In accomplishing the CLIRAM for seasonal valuesdetermine the projected patterns of change(Column 7 of Table 1) based on the following(refer to Columns 4 to 6):

1. The lower bound that indicates the lowest possible change;

2. The upper bound that indicates the highest possible change; and

3. The median which represents multi model central estimate the future change.

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Example(of(the(filled(up(CLIRAM(for(different(sectors(in(Salcedo

(

Percent'(%)Rainfall'amount'

(mm)Col'1 Col'2 Col'3 Col'4 Col'5 Col'6 Col'7 Col'8 Col'9

Lower(Bound =4.2 =41.1 945.9 Minimal(to(no(change

Median 1.3 12.5 999.5 Minimal(to(no(change

Upper(Bound 45.0 444.4 1431.4

The(highest(possible(future(rainfall(change(during(the(

Northeast((NE)(Monsoon(or(Amihan(shows(an(increase(

of(45%(.(This(increase(could(be(detrimental(to(some(

sectors(of(the(community,(as(this(season(corresponds(

to(the(wettest(months(over(the(region(

●(Farm(Flooding,Crops(ruined((e.g.(

wash(out(of(planted(cassava(6=8(months(

growing(period)

●(Pest(&(Disease(Infestation

●(Increased(Cost(of(lodging(animals(&(

crops

●(Decrease(in(yield(/production


Median 13.7 135.2 1122.2 Minimal(increase

Upper(Bound 43.6 430.8 1417.8

The(highest(possible(future(rainfall(change(during(the(

Northeast((NE)(Monsoon(or(Amihan(shows(an(increase(

of(44%.(This(increase(could(be(detrimental(to(some(

sectors(of(the(community,(as(this(season(corresponds(




growing(period)



crops


CLIRAM:(Projected(Changes(in(Seasonal(Rainfall(in(the(Mid=21st(Century((2036=2065)(for(Eastern(Samar(relative(to(1971=2000(((((((((((

•Extend(cover/greenhouse(style(of(planted(crops

•Plant(water(resistant(varieties,(raise(beds,(transfer(

planting(sites

•Provide(good(farm(drainage,(by(construction(of(

irrigation(canals(to(divert(excess(surface(run=off

•(Practice(cut&carry,(provide(permanent(shelter(to(

livestock

•(Use(flood(tolerant(/(water(resistant(

varieties/drought(tolerant(varieties

•(Conduct(Climate(Field(School(to(make(farmers(

more(resilient(to(climate(adversities

•(Provide(EWS(for(agriculture

•(Provide(insurance(to(farmers

Agriculture

December=

January=February(

(DJF)(((((((

((((((((((((((((((((

Observed(

baseline(=((987(

mm

Moderate(

Emission(

(RCP(4.5)

High(Emission(

(RCP(8.5)

Same(vulenrability(to((the(present

Season Scenario Range*Projected'Change Projected'

Seasonal'Rainfall'Amount'

(mm)

Information'about'patterns'of'changePotential'Impacts

Adaptation'Option


Example of a filled-up CLIRAM for Agriculture sectors in Salcedo

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Example(of(the(filled(up(CLIRAM(for(different(sectors(in(Salcedo

(

Percent'(%)Rainfall'amount'

(mm)Col'1 Col'2 Col'3 Col'4 Col'5 Col'6 Col'7 Col'8 Col'9



Upper(Bound 45.0 444.4 1431.4

The(highest(possible(future(rainfall(change(

during(the(Northeast((NE)(Monsoon(or(

Amihan(shows(an(increase(of(45%(.(This(

increase(could(be(detrimental(to(some(sectors(

of(the(community,(as(this(season(corresponds(




growing(period)



crops



Median 13.7 135.2 1122.2 Minimal(increase

Upper(Bound 43.6 430.8 1417.8

The(highest(possible(future(rainfall(change(

during(the(Northeast((NE)(Monsoon(or(

Amihan(shows(an(increase(of(44%.(This(

increase(could(be(detrimental(to(some(sectors(

of(the(community,(as(this(season(corresponds(




growing(period)



crops




Upper(Bound 17.4 80.8 544.9 Minimal(increase

Lower(Bound 5.8 26.8 490.9 Minimal(to(no(change




Median =1.1 =6.0 553.8 Minimal(to(no(change

Upper(Bound 8.3 46.4 606.2 Minimal(to(no(change

Lower(Bound =14.0 =78.3 481.5 Minimal(reduction



Lower(Bound =20.1 =174.9 696.5

The(driest(possible(future(rainfall(change(

during(the(transition(period(from(NE(to(SW(

monsoon(shows(a(reduction(of(20%

Median =16.6 =144.7 726.7

The(most(likely(future(rainfall(change(during(

the(transition(period(from(NE(to(SW(monsoon(

shows(a(reduction(of(17%

Upper(Bound =3.8 =33.4 838.0 Minimal(to(no(change

Lower(Bound =22.0 =191.3 680.1

The(driest(possible(future(rainfall(change(

during(the(transition(period(from(NE(to(SW(

monsoon(shows(a(reduction(of(22%


Upper(Bound 4.7 40.7 912.1 Minimal(to(no(change

*(upper:(90th(percentile;(median:(50th(percentile;(lower:(10th(percentile

September=

October=

November((SON)(((((((((((((((((((((((((((((((((((((((((((((

Observed(

baseline(=((871(

mm

CLIRAM:(Projected(Changes(in(Seasonal(Rainfall(in(the(Mid=21st(Century((2036=2065)(for(Eastern(Samar(relative(to(1971=2000(((((((((((

Season Scenario Range*Projected'Change Projected'

Seasonal'Rainfall'Amount'

(mm)

Information'about'patterns'of'changePotential'Impacts

Adaptation'Option

Moderate(

Emission(

(RCP(4.5)

High(Emission(

(RCP(8.5)

•Extend(cover/greenhouse(style(

of(planted(crops

•Plant(water(resistant(varieties,(

raise(beds,(transfer(planting(sites

•Provide(good(farm(drainage,(by(

construction(of(irrigation(canals(to(

divert(excess(surface(run=off

•(Practice(cut&carry,(provide(

permanent(shelter(to(livestock

•(Use(flood(tolerant(/(water(

resistant(varieties/drought(

tolerant(varieties

•(Conduct(Climate(Field(School(to(

make(farmers(more(resilient(to(

climate(adversities

•(Provide(EWS(for(agriculture

•(Provide(insurance(to(farmers

June=July=August(

(JJA)((((((((((((((((((((((((

Observed(

baseline(=((560(

mm

Moderate(

Emission(

(RCP(4.5)


High(Emission(

(RCP(8.5)

March=April=May(

(MAM)((((((((((((

(((((((((((((((((((((((((Ob

served(baseline(=((

464(mm

Moderate(

Emission(

(RCP(4.5)

High(Emission(

(RCP(8.5)


Water(is((sufficient(for(farming(activity

December=

January=February(

(DJF)(((((((

((((((((((((((((((((

Observed(

baseline(=((987(

mm

Moderate(

Emission(

(RCP(4.5)

High(Emission(

(RCP(8.5)

Agriculture

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Example(of(the(filled(up(CLIRAM(for(Agriculture(in(Salcedo

Change'in'�Projected'Seasonal'Mean'Temperature'

(�)'Col'1 Col'2 Col'3 Col'4 Col'5 Col'6 Col'7 Col'8Lower(Bound 1.0 27.1 Coldest(season

Median 1.1 27.2 27.1(to(27.7

Upper(Bound 1.6 27.7Lower(Bound 1.3 27.4

Median 1.5 27.6 27.4(to(28.0Upper(Bound 1.9 28.0

Lower(Bound 1.0 28.7

Median 1.2 28.9 28.7(to(29.4

Upper(Bound 1.7 29.4




Median 1.2 29.5 29.3(to(30.1


Lower(Bound 1.4 29.7 Hottest(season

Median 1.7 30.0 29.7(to(30.5Upper(Bound 2.2 30.5Lower(Bound 1.0 28.7

Median 1.2 28.9 28.7(to(29.5




*(upper:(90th(percentile;(median:(50th(percentile;(lower:(10th(percentile

Generally((all(seasons(becoming((warmer(,(in(which(Air(surface,(soil(and(groundwater(temperatures(will(be(warmer.(The(general(climate(effects(of(having(warmer(oceans(or(lakes(are(included(here.(Increase(in(temperature((ranging(from(1.0(to(2.2(degrees(•(Impotent(livestock/crops(•(Livestock(disease(•(Decrease(in(yield(/production((•(Ice(Ice(effect(•(Fish(Kill

CLIRAM:Projected(Changes(in(Seasonal(Temperature(in(the(Mid\21st((Century((2036\2065)(for(Eastern(Samar(relative(to(1971\2000(((((((((((

Season Scenario Range*Projected'Change Information'about'

patterns'of'change Potential'Impacts

Adaptation'Option

Agriculture

December\January\February((DJF)(((((((

((((((((((((((((((((Observed(baseline(=((

26.1(�

Moderate(Emission((RCP4.5)

High(Emission((RCP8.5)

(•(Conduct(Climate(Field(School(to(make(farmers(more(resilient(to(climate(adversities•(Provide(EWS(for(agriculture•(Provide(insurance(to(farmers•(Translating(the(temperature(changes(to(impacts(to(different(crops

March\April\May((MAM)(((((((((((((((((((((((((((((((((((((Observed(baseline(=((27.7(�



June\July\August((JJA)((((((((((((((((((((((((

Observed(baseline(=((28.3(�



September\October\November((SON)(((((((((((((((((((((((((((((((((((((((((((((

Observed(baseline(=((27.7(�



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y"=" $0.7347x"+"435.03

0

200

400

600

800

0.0 50.0 100.0 150.0 200.0 250.0 300.0

DAVAO"REGIONMay"Rainfall"vs"Mangostin

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COMPONENTS

Component A: Risk and Vulnerability Assessment

Component B: GHG Inventory and Review of Current Mitigation Actions

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Key questions and elements for Component A in Step 3Step 3 LCCAP

Component A: Climate Change Vulnerability and Risk Assessment

Key Questions:

1. Vulnerabilities, Risks, and Opportunities of climate change in communities

2. Types of climate-related and natural hazards

3. Issues that need to be addressed,

4. Location of climate change issues and hazards- current and are projected to happen (illustration/mapping)

5. Summary description on type of climate related hazards and issues will the LGU face in the future?

6. Analysis report on why and when should action be initiated

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Activity Objectives:

• To be able to interpret the projected climate changes in the area assigned to you

• To identify the potential impacts of projected changes and provide possible adaptation options using the CLIRAM for seasonal rainfall and mean temperature

Ø Determine the projected patterns of change in seasonal rainfall. Provide your inputs in Column 7 by referring to the information provided in Columns 4 to 6 of the CLIRAM:• The lower bound indicates the driest possible change;• The upper bound indicates the wettest possible change; and• The median represents the multimodel central estimate of future change

Ø Identify the sectors affected by the changes, potential impacts of projected changes and adaptation options

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Projected Changes in Seasonal Rainfall in the Mid-21st Century (2036-2065) for Metro Manila relative to 1971-2000

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Projected Changes in Seasonal Rainfall in the Mid-21st Century (2036-2065) for Metro Manila relative to 1971-2000

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Pampanga

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Albay

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Leyte

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Misamis Oriental

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Davao del Norte

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Acknowledgements

Thelma A. Cinco, Emma D. Ares, Marcelino Q. Villafuerte II, John A. Manalo, Wilmer Agustin,Kimberli Anne Aquino

Joseph Daron, Richard Jones, Ian Macadam, Florian Gallo, Ron Kahana, Claire Scannell, David Hein, Simon Tucker, Rosanna Amato, and David Corbelli;

Jack Katzfey and Dewi Kirono.

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http://www.pagasa.dost.gov.ph/

www.facebook.com/PAGASA.DOST.GOV.PH

@dost_pagasa

Thank you! JContact us: Impact Assessment and Application Section

Climatology and Agrometeorology Division, DOST-PAGASA

+632-434-58-82/434-8130

Thelma A. Cincoemail: [email protected]

mailto:[email protected]

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Day 1 - Observed Climate Trends and Projected Climate Change … · Payong PAGASA PAGASA The...

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